Compound Identification Using Penalized Linear Regression on Metabolomics

Authors

Ruiqi Liu, University of LouisvilleFollow
Dongfeng Wu, University of LouisvilleFollow
Xiang Zhang, University of LouisvilleFollow
Seongho Kim, Wayne State UniversityFollow

Abstract

Compound identification is often achieved by matching the experimental mass spectra to the mass spectra stored in a reference library based on mass spectral similarity. Because the number of compounds in the reference library is much larger than the range of mass-to-charge ratio (m/z) values so that the data become high dimensional data suffering from singularity. For this reason, penalized linear regressions such as ridge regression and the lasso are used instead of the ordinary least squares regression. Furthermore, two-step approaches using the dot product and Pearson’s correlation along with the penalized linear regression are proposed in this study.

DOI

10.22237/jmasm/1462076340